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What Vulnerabilities? How (And Why) to Secure Your ML/AI Solutions

Because our models and pipelines don’t usually run in production, it's natural to put less scrutiny into the security of the systems and the code. However, vulnerabilities in our data architecture, software architecture, or network design can expose critical company IP or personal data to hackers or fraudsters. Vulnerabilities in the open-source packages we use to build our models can be exploited as well. This talk covers considerations around security that should be central to anyone building ML/AI solutions.
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